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The Impact of GenAI on Modernizing Food & Beverage Operations

RandomTrees

The food and beverages (F&B) industry has been transformed digitally, resulting from new technology, including GenAI. In this blog, we will look at some of the approaches GenAI has advanced in food and beverage, supported by relevant research statistics as well as real-life experiences and case studies in detail.

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Data Structures and Algorithms (DSA) Projects with Source Code

Knowledge Hut

Data structures and algorithms are the building blocks of effective software in computer science and programming. We shall also discuss various data structures and algorithm projects with source code. What is an Algorithm? Software engineers need to understand algorithms to design dependable and effective code.

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Classification vs. Regression Algorithms in Machine Learning

ProjectPro

They are built using Machine Learning algorithms. These algorithms majorly fall into two categories - supervised algorithms and unsupervised algorithms. While supervised algorithms comprise data with labels, unsupervised algorithms have unlabelled data. Yes, you are right. Regression. What is Classification?

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Data Science in Agriculture: Roles, Application, Examples

Knowledge Hut

Food Safety Finally, Data Science is also playing a role in food safety. By analyzing food-borne illness data, agricultural scientists can identify risk factors and develop strategies for reducing the spread of disease-causing bacteria. This helps to protect consumers and ensure that food products are safe for consumption.

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Improving ETAs with Multi-Task Models, Deep Learning, and Probabilistic Forecasts

DoorDash Engineering

We want to ensure that every customer can trust our ETAs, ensuring a high-quality experience in which their food arrives on time every time. Initially, customers can use ETAs on the home page to help them decide between restaurants and other food merchants. This unpredictability can affect out accuracy.

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Container Runtime: GPU Training & Inference with Snowflake Notebooks

Snowflake

Recommendation engine : In this example, a global food truck company is looking to build a recommendation engine to power hundreds of food trucks to generate highly accurate, hyper-local menu recommendations. We demonstrate how, using a PyTorch-based recommendation algorithm, you can train and deploy a model to do exactly that.

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Lifecycle of a Successful ML Product: Reducing Dasher Wait Times

DoorDash Engineering

Scoping out the business problem: optimizing food prep times Before our ML development journey starts we have to scope out the business problem and try to identify an opportunity for improvement. One example is around delayed food prep times that increase Dasher wait times. When do restaurants start preparing food?

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